Search Results - (( intelligence based vs algorithm ) OR ( intelligence based ((a algorithm) OR (_ algorithm)) ))

Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

“…Two case studies are used to evaluate those algorithms, and the camera placement problem is formulated as a coverage maximization problem. …”
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Visualization of dengue incidences using expectation maximization (EM) algorithm by Mathur, N., Asirvadam, V.S., Dass, S.C., Gill, B.S.

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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

“…At first, in producing a good optimization algorithm, a hybridization technique was proposed for adopting the finest features of two different algorithms; namely the Genetic Algorithm (GA) and continuous domain Ant Colony Optimization (ACOr). …”
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Evaluation of intracerebral haemorrhages surface area using artificial intelligence in computed tomography by Huddin, Azzam Basseri, Huddin, Aqilah Baseri, Tharek, Anas, Wan Zaki, Wan Mimi Diyana, Muda, Ahmad Sobri

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Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation by Kamal Z., Zamli, Ahmed, Bestoun S., Mahmoud, Thair, Afzal, Wasif

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Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

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Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft by Abro, G.E.M., Bin Mohd Zulkifli, S.A., Asirvadam, V.S.

“…The simulation work for proposed algorithm is performed using MATLAB and Simulink that are compared with conventional sliding mode control (SMC) and fuzzy-based SMC control techniques. …”
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DNA sequence design for direct-proportional length-based DNA computing: Particle swarm optimization vs population based ant colony optimization by Zulkifli, Md. Yusof, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi, Kamal, Khalil, Zuwairie, Ibrahim

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Comparing deep learning CNN method with traditional MRI-based hippocampal segmentation and volumetry for early Alzheimer’s disease diagnosis across diverse populations by Ibrahim, Nur Shahidatul Nabila, Suppiah, Subapriya, Ibrahim, Buhari, Mohad Azmi, Nur Hafizah, Seriramulu, Vengkatha Priya, Mohamad, Mazlyfarina, Hanafi, Marsyita, Mohammad Sallehuddin, Hakimah, Omar Sharif, Nurallysha Najwa, Razali, Rizah Mazzuin, Harrun, Noor Harzana

“…We utilized HippoDeep, an open-source CNN-based algorithm, to compare the MRI-derived hippocampal volumes from a Caucasian population dataset with a Southeast Asian AD and cognitively healthy control (HC) population dataset. …”
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Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft by Abro, G.E.M., Bin Mohd Zulkifli, S.A., Asirvadam, V.S.

“…The simulation work for proposed algorithm is performed using MATLAB and Simulink that are compared with conventional sliding mode control (SMC) and fuzzy-based SMC control techniques. …”
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Content-based indexing of low resolution documents by Md Nor, Danial

“…The assessment of the proposed indexing scheme is conducted based on recall and precision, a standard CBIR retrieval performance evaluation. …”
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Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

“…A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. …”
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Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

Subjects: “…Intelligent water drops algorithm…”

Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

“…In this work active intelligent control comprises a set of control techniques based on particle swarm optimisation (PSO), real coded genetic algorithm (RCGA) and artificial immune system (AIS). …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Stereo matching algorithm based on deep learning: a survey by Hamzah, Rostam Affendi, Hamid, Mohd Saad, Kadmin, Ahmad Fauzan, Abd Manap, Nurulfajar

“…Hence, this article presents a survey on the algorithm frameworks related to the stereo matching algorithm. …”
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Integration of dual intelligent algorithms in shunt active power filter by Abdul Rahman, Nor Farahaida, Mohd Radzi, Mohd Amran, Mariun, Norman, Che Soh, Azura, Abd Rahim, Nasrudin

“…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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Intelligent Examination Timetabling System Using Hybrid Intelligent Water Drops Algorithm by AlDeeb, BA, Norwawi, NM, Al-Betar, MA, Jali, MZ

“…Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops. …”

A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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